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APPLIED AI SCIENTIST - INTERN
The ZAIDYN platform team is driving the development and commercialization of a robust ecosystem of AI and Generative AI products across industries.
We are seeking a highly motivated Applied AI Scientist Intern with a strong foundation in Machine Learning and a deep interest in Large Language Models (LLMs) and Generative AI. This role focuses on building, optimizing, and evaluating production-grade LLM systems, including Retrieval-Augmented Generation (RAG), fine-tuning workflows, and scalable inference pipelines.
What You'll Do
- Design and implement LLM-powered applications using state-of-the-art transformer models.
- Build and optimize RAG pipelines using embeddings, chunking strategies, and vector search.
- Experiment with prompt engineering, structured outputs (JSON schemas/function calling), and tool-augmented LLMs (agents/workflows).
- Fine-tune models using techniques such as LoRA, PEFT, and instruction tuning.
- Develop and evaluate embedding models for similarity search and semantic retrieval.
- Conduct LLM evaluation using automated and human-in-the-loop techniques (offline + online).
- Optimize inference workflows for latency, GPU utilization, and cost efficiency (quantization, batching, caching).
- Build and maintain REST API Services (FastAPI etc.) to deploy LLM/RAG endpoints, integrate with product systems, and support scalable inference.
- Contribute to integration of AI systems into production software environments (CI/CD, monitoring, reliability).
- Research and prototype cutting-edge approaches in Generative AI and share learnings with the team.
What You'll Bring
- Candidates should be pursuing a master's degree in Artificial Intelligence, Computer Science, Statistics, or a related field with strong academic performance in analytic and quantitative coursework;
- Strong foundation in Machine Learning, Deep Learning, Neural Networks, Transformer architecture, self-attention mechanisms, pretraining vs. fine-tuning, and instruction tuning
- Hands-on experience with either LLM Frameworks (Hugging Face, OpenAI APIs, vLLM, etc.) and/or PyTorch / TensorFlow
- Familiarity with Embedding models, Vector databases, RAG architectures, Prompt engineering best practices, LLM evaluation techniques, Inference optimization (quantization, batching)
Additional Skills
- Good to have: LangChain, LangGraph, Langfuse (observability/evals), and related tooling for orchestration and monitoring
- Excellent oral and written communication skills;
- Strong attention to detail, with a research-focused mindset;
- Excellent critical thinking and problem-solving skills;
- High motivation, good work ethic and maturity.
At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you'll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community . For details on total rewards in United States , visit ZS US office locations | Where we work | ZS .
Salary: $6,000.00 - $6,000.00
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What We Do
ZS is a management consulting and technology firm that partners with companies to improve life and how we live it. We transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Founded in 1983, ZS has more than 15,000+ employees in over 40 offices worldwide.
Why Work With Us
ZS is home to passionate people who embrace innovative thinking, collaboration and a client-first mindset. Welcome to a company where new ideas are celebrated, curiosity is welcomed, learning opportunities are abundant and colleagues become lifelong connections.
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